Discover some of the most common software engineering job interview questions on data structures and algorithms. Use this guide to help you prep!
Here’s what we’ll cover:
Data structures and algorithms are a complex part of computer science theory. This is perhaps why they’re a favorite among hiring managers in interview settings for software engineering roles.
This guide features sample interview questions curated from real hiring experiences to better prepare you for your next software engineering interview.
Python is a versatile and dynamic programming language that is easy for humans to read and write. That makes it a perfect hiring interview language to work with since most interviews will involve many constraints and you’ll have to express your code and logic clearly without any help.
You might have to write down your code on paper, for example, or repeat it vocally over the phone. Python lends itself well to those situations.
Below are some sample Python data structures and algorithms questions you can expect in a software engineering hiring interview.
Answer: You should know the answer about these default data structures in Python as it’s frequently asked. In short, lists are mutable (they can be modified) while tuples are immutable (they cannot be modified). Lists are ordered by one central index, while a tuple may hold multiple data types together in an index-like-form.
Answer: This question tests your grasp of the implications for Python data structures and the algorithms you can implement on top of them. Lists are slower for lookups: it’ll take O(N) time since filtering through for a value will require as a worst-case scenario filtering through every value in the list. Dictionaries are well-set up with key-value pairs, similar to a hash table. Thus the time to search will be O(1) as long as you have the correct key.
Answer: There are three different ways to do this: via a yield function, a list comprehension, or a for loop. All three are demonstrated here.
Answer: List comprehensions are a feature in Python that allows us to work with algorithms within the default list data structure in Python. Here, we’re looking for odd numbers.
A list comprehension allows us to simplify our range and filtering algorithm so we can pack it into one line of code—return every element in the range between 0 and 100, if it divides perfectly by 2.
Be prepared to describe the list comprehension in detail with the right notation if you need to write it down on paper, or recite it over the phone as coding interviews sometimes demand.
Answer: This is a tricky one. When it comes to Python algorithms, a lot of the work is usually abstracted away by the built-in default data structures or easy methods that can be called in one line. However, regular expression algorithms, used for filtering through selections of text, are often some of the most difficult to grasp. You’ll have to get familiar with regular expression rules in Python to be able to write out the answer.
Only by ensuring that everything that interacts with the + operator is a number or BigInt data type can you ensure that a desired behavior of addition happens.
Answer: You have to use the default .push() method in order to add something at the end of an array, while you can use the default .unshift() method in order to add something at the beginning. In practice, knowing this answer helps prove that you understand how arrays fundamentally work.
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